Software Engineer, Conversion Measurement

United States Digital Space LLC; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Relocation assistance

Job summary

OpenAI's Monetization team seeks an experienced Software Engineer to build measurement systems that connect ad interactions to advertiser outcomes while safeguarding user privacy. You will design infrastructure for conversion signals, attribution, reporting, and feedback loops across the company’s ads products.

This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, or distributed systems and want to apply that experience in a highly ambiguous 0→1

Qualifications

• 10+ years of experience building and operating large-scale distributed data or backend systems.
• Experience with conversion-event pipelines, attribution, deduplication, identity and matching, reporting, or related signals.
• Privacy-safe measurement design, including aggregation, consent handling, modeled conversions, or clean-room patterns.
• Ability to reason about data correctness, delayed/out-of-order events, and metric discrepancies.
• Experience with high-throughput batch or streaming systems and relevant tradeoffs.
• Collaboration with ML and data science for labels, experimentation, and causal measurement.
• Holistic architectural thinking with emphasis on privacy, trust, and advertiser value.
• Capacity to define direction in ambiguous 0→1 environments and drive cross-team work.
• Clear communication and decisions grounded in user value and system health.

Responsibilities

• Design and operate large‑scale conversion measurement systems across ads stack.
• Implement privacy‑preserving identity, matching, aggregation, and reporting.
• Develop scalable instrumentation for conversions, attribution windows, deduplication, and signal loss mitigation.
• Create data quality systems to detect missing, duplicated, or misconfigured signals.
• Build advertiser reporting and diagnostics for conversions, CPA, ROAS, and health metrics.
• Collaborate with Ads ML on labels and feedback loops for ranking, bidding, and budget optimization.
• Advance experimentation capabilities including holdouts and causal measurement foundations.
• Define technical strategy and roadmap for conversion measurement across delivery systems.
• Operate with rigorous testing, observability, privacy reviews, and incident response.

Skills

Large-scale distributed systems

Ads measurement / attribution

Privacy-preserving measurement

Data quality & correctness

Collaboration with ML & Data Science

Holistic system thinking

Strong communication

Job description

About the Team

The Monetization team is a cross‑functional group working across engineering, product, research, and design to build the foundational systems that will help the company scale access to intelligence responsibly. Our mission is to develop user‑first, privacy‑preserving monetization products, including next‑generation ads experiences that strengthen user trust, unlock economic opportunity, and support the company’s long‑term innovation.

Monetization plays a critical role in enabling the company to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.

This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real‑world systems at global scale.

About the Role

We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across the company’s ads products.

This role is ideal for engineers who have built large‑scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy‑safe aggregation, reporting, and high‑quality labels for ads optimization.

We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Science, Design, and advertiser‑facing teams to create trustworthy measurement from first principles.

This role is based in San Francisco or Seattle. We offer relocation assistance to new employees.

Responsibilities

• Design and build reliable conversion‑event collection and processing systems across pixels, SDKs, server‑side APIs, app events, offline uploads, and advertiser integrations.
• Build attribution and measurement infrastructure for observed and modeled conversions, attribution windows, deduplication, delayed events, and signal‑loss mitigation.
• Develop privacy‑preserving identity, matching, aggregation, and reporting systems that provide useful measurement under strict privacy constraints.
• Create data‑quality systems that detect missing, duplicated, malformed, out‑of‑order, fraudulent, or misconfigured conversion signals.
• Build scalable advertiser reporting and diagnostics for conversions, cost per action, return on ad spend, funnel performance, and measurement health.
• Partner with Ads ML to deliver trustworthy conversion labels and feedback loops for ranking, bidding, targeting, and budget optimization.
• Develop experimentation and incrementally capabilities, including holdouts, lift studies, and causal measurement foundations.
• Define the technical strategy and roadmap for conversion measurement across the company’s ads delivery stack.
• Operate systems with high engineering rigor through testing, observability, privacy reviews, incident response, and operational best practices.

Qualifications

• Have 10+ years experience building and operating large‑scale distributed data or backend systems, ideally in ads measurement, attribution, analytics, marketplaces, experimentation, or adjacent domains.
• Understand conversion‑event pipelines, attribution, deduplication, identity and matching, reporting, or downstream optimization signals.
• Have experience designing privacy‑safe measurement systems, including aggregation, consent handling, modeled conversions, clean‑room patterns, or privacy‑preserving APIs.
• Can reason about data correctness, delayed and out‑of‑order events, schema evolution, reconciliation, and internal‑versus‑external metric discrepancies.
• Have built high‑throughput batch or streaming systems and can make sound tradeoffs across latency, reliability, cost, and maintainability.
• Are comfortable partnering with ML and data science teams on labels, model inputs, experimentation, and causal measurement.
• Think holistically across architecture, product semantics, data quality, observability, privacy, and advertiser trust.
• Can define technical direction in an ambiguous 0→1 environment and independently drive complex work across teams.
• Communicate clearly and make technical decisions grounded in user value, system health, measurement credibility, and long‑term product direction.

Background & Company Information

OpenAI is an AI research and deployment company dedicated to ensuring that general‑purpose artificial intelligence benefits all of humanity. We push the boundaries of AI systems and seek to safely deploy them to the world through our products.

AI is an extremely powerful tool that must be created with safety and human needs at its core. To achieve our mission, we value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or any other applicable legally protected characteristic.

Background Checks & Legal Information

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US‑based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non‑public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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